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Data Science Lead R
Job Location:
Monthly Salary:
Posted:
29 September 2026 (18 hours ago)
Posted:
Application Deadline:
27 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Data Science Lead
Job requirements
- Design and implement advanced machine learning and AI solutions including LLM-based applications and agentic AI systems to address complex business challenges and deliver measurable business outcomes
- Lead the development deployment and operation of production AI/ML and GenAI models across major cloud platforms such as Azure AWS or GCP ensuring high availability and scalability
- Build orchestrate and optimize AI agents and autonomous workflows focusing on robust memory context management and multi-agent architectures
- Drive enterprise AI/ML workloads within the Databricks ecosystem leveraging Databricks AI Agents Model Serving Vector Search MLflow and Unity Catalog to enhance operational efficiency
- Establish and maintain MLOps and LLMOps practices including CI/CD pipelines model lifecycle management experiment tracking evaluation and monitoring for continuous improvement
- Develop and apply RAG architectures embeddings vector databases prompt engineering and LLM evaluation frameworks to improve model performance and reliability
- Ensure AI security responsible AI practices data privacy and effective mitigation of hallucination prompt injection and GenAI guardrails
- Mentor engineers and provide technical leadership collaborating with cross-functional teams to deliver scalable enterprise-grade AI solutions
- Advanced hands-on programming experience in Python
- Proficiency in SQL and experience with large-scale structured and unstructured datasets
- Strong practical understanding of machine learning and AI fundamentals
- Hands-on experience building and deploying LLM-based applications
- Expertise in agentic AI including agent orchestration autonomous workflows tool/function calling planning task decomposition memory and context management
- Extensive hands-on experience with Databricks AI Agents and the Databricks ecosystem
- Experience with MLOps and LLMOps including CI/CD model lifecycle management experiment tracking and production deployment
- Proven experience deploying and operating AI/ML or GenAI models/applications in Azure AWS or GCP
- Expertise in RAG architectures embeddings vector databases/vector search prompt engineering and LLM evaluation
- Proficiency with LLM and GenAI frameworks/orchestration tools such as LangChain LangGraph Semantic Kernel or similar technologies
- Experience building enterprise-grade agentic AI platforms or multi-agent systems
- Expertise with Databricks Model Serving Vector Search MLflow Unity Catalog and related Databricks AI/ML capabilities
- Experience with Kubernetes Docker REST APIs microservices and CI/CD pipelines
- Experience with managed GenAI platforms such as Azure OpenAI AWS Bedrock or Google Vertex AI
- Experience with vector databases like Pinecone Azure AI Search Weaviate or Databricks Vector Search
- Experience optimizing LLM applications for latency throughput scalability token consumption and cost
- Bachelors degree in Computer Science Data Science Artificial Intelligence Information Technology or a closely related discipline
- Certification in machine learning AI engineering or data science from a recognized institution such as TensorFlow Developer Certificate or Databricks Certified Professional Data Scientist
- Certification in cloud platforms or MLOps for example AWS Certified Machine Learning Specialist or Azure AI Engineer Associate
Experience Range: With at least 8 years of experience in AI/ML engineering machine learning data science software engineering or related fields Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
About Company
Brillio is a global leader in Enterprise Digital Transformation Solutions, providing strategic consulting services and solutions using emerging technologies.
